UX CASE STUDY · AI · May 2024 - June 2025
Cutting court transcript turnaround 90% with offline AI under strict government privacy laws.
External contractors were drowning in manual audio work and delays stretched to weeks. I designed and built a fully offline AI transcriber that runs on court hardware, generates same-day dirty transcripts, and opens a direct revenue stream without adding headcount.
Word about my Transcript Workflow Manager got around the courthouse, and court leadership contacted me directly to build an AI transcription tool. I owned the research, the ML pipeline, and the interface design.
The Problem vs. The Solution
Courtroom audio was a black box. Over 100 hours of unindexed recordings sat in storage, clerks manually scrubbed through tapes, and requesters paid $9.25 a page for transcripts that took days to arrive.
The transcription backlog
Court clerks waited days, sometimes weeks, for external contractors to manually transcribe audio. Every cloud-based AI tool that could have helped was legally off-limits.
Offline AI automation
A Python desktop app that runs entirely on local court hardware, fits how clerks already work, and outputs a timestamped transcript in hours. No internet required.
The Impact
Going offline-first was the unlock. Cutting out third-party vendors freed budget, earned trust from leadership, and gave the courts a way to generate revenue on their own terms.
Transcription turnaround time
Key Design Decisions
Three calls that shaped the system, each forced by a legal, trust, or business constraint rather than a preference.
The whole pipeline runs on local court hardware with offline WhisperX models. No byte ever leaves the device.
Government privacy policy prohibited every commercial cloud AI tool on the market. Running local was the only legal path, and it removed the security review question entirely.
A verification layer lets clerks review AI output before a transcript goes anywhere.
Courtroom audio is messy and AI output cannot be treated as gospel in a legal setting. Clerks owning the final check is what made the tool trustworthy enough to use.
The product is a rough, timestamped same-day transcript offered at a much lower price than vendor transcripts.
Vendors were permanently booked and charged $9.25 a page. A cheap preliminary transcript could ship in hours and become court revenue without hiring anyone.
From Wireframe to Running Portal
The interface started as three wireframe concepts in Figma, judged against how clerks already search, then became a running desktop prototype.
Try the AI Transcriber
This is the real thing. Load a file, watch it process, and explore the full output interface, exactly as it was designed and shipped.
My deep dive into AI, and into selling the work
This project taught me AI development from the inside: tensors, transformers, beams, weights, and tuning parameters for courtroom acoustics. Testing meant live court sessions with clerks reading Casablanca into the record. It also taught me to present, since I spent as much time demoing to stakeholders and contractors as I did tuning models. The Flutter interface never shipped because the project paused while HQ made decisions, and I learned that in government work, the pitch and the pipeline matter equally.
Let's build something impactful.
I'm currently open to new opportunities in UX/UI Design, Product Design, and GovTech transformation roles.